1. Field of the Invention
The present invention relates to a method and system for data management in communication networks.
2. Description of the Related Art
As stated by Sasikanth, Avancha et al. (“Data and Services for Mobile Computing”, Practical Handbook of Internet Computing, M. P. Singh ed., pages 1-18) the term “computing device” or “computer” usually evokes the image of a big, powerful machine located in an office or home, that is always on and possibly connected to the Internet. The advent and phenomenal growth of low-cost, lightweight, portable, easily and constantly available devices, even when one is on the move, has altered this image. The combination of device mobility and computing power has resulted in the Mobile Computing paradigm. The smaller the devices, the greater their portability and mobility, but lesser their computing capability.
Accordingly, evolutionary service scenarios (e.g. in near-future cities, industrial/financial areas, etc.) will be characterized by proliferation of different portable devices like cell phones, PDAs, laptops, sensors, RFID (Radio Frequency Identification) tags and other miniaturized transmitters, commonly and increasingly linked by wired and wireless connectivity.
Digital devices, miniaturized and highly dispersed handsets are expected to create a blanket of interconnected resources that can offer huge amounts of data available to capture “social” dynamics/needs. These data, properly collected, correlated and managed are valuable to enable more effective service execution and provisioning. For example, mobile devices could interact with their neighbours and act as both information producer and consumer according to needs.
The scenario described above allows envisioning a pervasive digital environment, very dynamic and data intensive where everyone can exchange information and collaborate to each others and where large amounts of highly distributed data items should be transformed, into meaningful, reliable and available information that each user can access anytime and anywhere using its mobile device.
Traditional data management models are not suitable to manage a so high dynamic and distributed environment strongly characterized by: data variation in space and time; lack of a global schema; and no guarantee about the duration of a connection among any pair of mobile devices.
In such an environment a data management layer adapted to enable a device to interact and exchange data with other devices located in its vicinity and elsewhere on the network, whilst ensuring the proper level of robustness, scalability and reliability, is strongly required.
The ultimate goal of the mobile computing paradigm is enabling people to accomplish tasks using computing devices, anytime, anywhere.
In order to address these requirements in the environment outlined above, the following challenging factors have to be taken into account: data are stored in heterogeneous devices; data are geographically distributed; data sources and user applications are mobile; data sources appear and disappear in an unpredictable way; data can have different meaning based on different usage and elaboration.
Data management layer in mobile computing applications deals with access, storage, monitoring, and data manipulation. This layer enables a device to interact and exchange data with other devices located in its vicinity and elsewhere on the network.
In order to allow a device to compute what information the device needs, when the device needs it, and how it can obtain the information, Filip Perich et al. (“Data Management for Mobile Ad-Hoc Networks”, InBook, Enabling Technologies for Wireless e-Business Applications, July 2005, W Kou and Yelena Yesha ed., Springer pub.) disclose a MoGATU peer-to-peer data management model for mobile ad-hoc networks.
As stated by Filip Perich et al., in a peer-to-peer model, all devices, mobile and static, are treated as peers. Mobile devices act as both servers and clients. Ad-hoc networking technologies, such as Bluetooth, allow mobile devices to utilize peer resources in their vicinity in addition to accessing servers on the wired network. Server mobility is, however, an important issue in this model. The set of services available to a client is dynamically changing with respect to location and time. Consequently, for obtaining data, devices cannot simply depend on a help of a fixed centralized server. Instead the devices must be able to cooperate with others in their vicinity in order to pursue individual and collective tasks. This allows devices to become more autonomous, dynamic and adaptive with respect to their environments.
The MoGATU model abstracts each peer device in terms of Information Providers, Information Consumers, and Information Managers.
Information Provider represent the available data sources. They represent entities able to accept some query and to generate proper response. Every Information Provider holds a partial distributed set, a fragment, of heterogeneous data available in the whole mobile ad-hoc network. Every device may hold one or more Information Providers.
Information Consumers represent entities that query and update data available in the environment. Information Consumers can represent human users asking their mobile devices for context-sensitive-information but also represent autonomous software agents. When a consumer needs to obtain a specific data, the consumer constructs an explicit query and sends it to its local Information Manager. The Manager routes the query to appropriate local Information Providers or other matching Providers located on remote peer devices for processing, and awaits a response.
Information Managers on every mobile device are responsible for network communication and for most of the data management functions. Each information Manager maintains information about Information Providers and Information Consumers present on the same device as the Information Manager. Each Information Manager also maintains information about peers in its vicinity. This information includes the identity of devices—a unique identification number similar to an Internet Protocol address, and types of information they can provide, i.e., Provider advertisements. Lastly, Information Manager maintains a data cache for storing information obtained from other mobile devices as well as the information provided by its local Providers, i.e., answers to previous queries. Additionally, each Information Manager may include a user profile reflecting the user's preferences and needs. The Information Manager uses the profile to adapt its caching strategy and to initiate collaboration with peers in order to obtain missing required information.
At a high complexity level, an Information Manager must be able to maintain information about multiple local and remote Information Providers, parse messages, route messages to other peer devices and pro-actively query peers. The MoGATU framework supports at the same time push and pull based approaches, i.e., each Information Manager can advertise its capabilities from solicit capabilities of other peers.